Learning Embeddings for Discrete Tree-Structured Data via Structural Prediction
Chen haoyang, Kumiko Tanaka-Ishii
Action editor: Yu Cheng

Learning Embeddings for Discrete Tree-Structured Data via Structural Prediction
Chen haoyang, Kumiko Tanaka-Ishii
Action editor: Yu Cheng
New #TMLR-Paper-with-Video:
Domain Adaptation for Cold-Start Users in Sequential Recommendation
Lu Wang, Wenyu Zhang, Wang Chengke, Guimei Liu, Ye Luo
Embeddings represent each item as a point in a high-dimensional space. Software compares distances between points to find related items without shared keywords. #Embeddings #SemanticSearch
Por qué te importa: Quien gestiona buscadores internos o archivos con imágenes y audio puede probar una misma consulta sobre todos esos formatos.
✅ 2 fuentes: Ollama releases y heise online – Künstliche Intelligenz
#IA #busquedamultimodal #embeddings
es.jumpdaily.news/modelos-y-chips/emb…
🤖How do embeddings help Generative AI?
🧠They turn information into vectors that power:
🔹 Semantic search
🔹 RAG applications
🔹 Smart recommendations
🔹 Context retrieval
🚀Explore the tools, benefits & challenges!
👉Read the full article: www.linkedin.com/pulse/how-do...
EmbeddingGemma 2:テキスト・画像・音声・動画を統合するオープンな軽量マルチモーダル埋め込みモデル
Google DeepMindが発表した「EmbeddingGemma 2」は、テキスト・画像・音声・動画を単一の空間にマッピングする7.4億パラメータのオープンな軽量マルチモーダル埋め込みモデルです。
Google DeepMind Releases EmbeddingGemma 2, a Local Multimodal Embedding for Text, Image, Audio and Video
New #J2C Certification:
The Linear Geometry of Interpretable Tokens: Jailbreaking Attacks and Defenses for Unlearned Diff...
Siyi Chen, Yimeng Zhang, Sijia Liu, Qing Qu
Gradient-based Sample Selection for Faster Bayesian Optimization
Qiyu Wei, Haowei Wang, Zirui Cao, Songhao Wang, Richard Allmendinger, Mauricio A Álvarez
Action editor: Jeff Phillips
🌎 Welcome LGND as a Bronze Sponsor of #FOSS4GNA
LGND builds #AI that understands the planet — turning #satellite imagery into searchable #embeddings so you can query the Earth in plain language, find similar features, and track change. No model training needed.
Learn more:
www.foss4gna.org/202...
В последнее время довольно много работаю над agent-memory-cpp.
Это C++ библиотека для быстрой, компактной и встраиваемой памяти AI-агентов: хранить embeddings локально и искать по ним без отдельного vector DB сервиса.
Un millón de #Embeddings de 1.024 dimensiones en float32: ~4 GB. Casi nunca hace falta tanto.
Matryoshka a 256 + binaria: ~32 MB, 128 veces menos. Y con rescoring recuperas buena parte de la calidad.
Mide contra el original: el ahorro que vale es el que no se nota en tu #RAG.
#PostgreSQL #in-process with #vectorsearch extensions directly #embedded in your #Python app. #OpenSource Apache 2.0 lic
- Similarly search: #pgvector + #pgvectorscale, high-performance storage
- #FullText search: #pg_textsearch, #BM25 and #ranking
#AI #LLM #Embeddings #Agents #RAG
New arXiv work shows scaling T5Gemma embeddings improves continuous diffusion language model performance, though highly discriminative raw embeddings can hurt sampling. Authors search for more diffusible embedding…
#GenerativeAI #DiffusionModels #LLM #Embeddings
https://arxiv.org/abs/2610.01016
Así se armó una app RAG con Gemini gratis, sin vector DB
Conocé el nuevo hito en IA: una app que implementa RAG con Gemini para respuestas más precisas y rápidas. Descubrí cómo funciona ahora mismo.
#ragcongemini #embeddings #geminiapi #nextjs #retrievalaugmentedgeneration
🚨 Confused by AI terms as a developer?
Clear guide to tokens, inference, embeddings, vector DBs & RAG! 🤖
📖 Guide: www.ottorinobruni.com/ai-basics-fo...
Which concept confuses you most? 👇
#dotnet #AI #RAG #Embeddings
Contractive MASO‑Generalized Predictors for Stable Latent‑Space Learning in JEPA
BELLOULATA
Action editor: Anastasios Kyrillidis
Including #Embeddings in Your #Spatial #Analysis Workflows tinyurl.com/4ud5zzhs
#data #datascience #GIS #esri #arcgis #GISchat #geospatial #mapping #ArcGISPro #geosky
🚨 Confused by AI terms as a developer?
Clear guide to tokens, inference, embeddings, vector DBs & RAG! 🤖
📖 Guide: www.ottorinobruni.com/ai-basics-fo...
Which concept confuses you most? 👇
#dotnet #AI #RAG #Embeddings
Learning Structured Set Utility Functions with Contrastive Element Representations
Jayanth Bhargav, Younggil Chang, Mahsa Ghasemi, Shreyas Sundaram
Action editor: Sebastian Tschiatschek